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  5. arrow_forward_ios UTS Business School makes investment in research

UTS Business School makes investment in research

26 February 2020

The UTS Business School has invested $130,000 in research infrastructure for use by its researchers. The money was invested to upgrade the high performance computing resources available for exclusive use by Business School researchers. The new resources will be administered and maintained as part of the UTS iHPC (Interactive High Performance Computing) facility.

The upgrade has been configured to meet the specific demands of Business School researchers who are working on research projects with large data sets which are memory and storage intensive. The upgrade has also been configured to meet current and future demands of Business School researchers who are undertaking research involving machine learning and deep learning models.

Due to capacity improvements resulting from the upgrade, our researchers will experience significant time savings on existing projects while also opening up opportunities to undertake research projects which are significantly more computationally intensive. The upgrade will also offer greater flexibility to researchers. Being configured with both CPU’s and GPU’s, the researchers will be able to make use of the option that will most efficiently run their programs.

The hardware acquired has been configured into four computational nodes. The specific configuration of each node is:

Nodes 1 to 3:

2 x Intel Xeon 6252 2.1 GHz 24 cores 35.75 MB L3 Cache (Max Turbo Freq. 3.7 GHz, Min 2.8 GHz)
384 GB 2933 MHz ECC DDR4-RAM (Six Channel)
2 x 1.8 TB 10,000 RPM SAS II Hard Drives (Raid 1) and 6 x 1.8 TB 10,000 RPM SAS II Hard Drives (Raid 10)
2 x NVIDIA Quadro RTX 5000 (3072 Cores, 384 Tensor Cores, 16 GB Memory) (GPU)

Node 4:

2 x Intel Xeon 6252 2.1 GHz 24 cores 35.75 MB L3 Cache (Max Turbo Freq. 3.7 GHz, Min 2.8 GHz)
768 GB 2933 MHz ECC DDR4-RAM (Six Channel)
2 x 1.8 TB 10,000 RPM SAS II Hard Drives (Raid 1) and 6 x 1.8 TB 10,000 RPM SAS II Hard Drives (Raid 10)
2 x NVIDIA Quadro GV100 (5120 Cores, 640 Tensor Cores, 32 GB Memory) (GPU)

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